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Image segmentation plays a crucial role in many medical imaging applications by automating or facilitating the delineation of anatomical structures and other regions of interest. Since the birth of the automated karyotyping systems by the aid of computers, building a fully automated chromosome analysis system has been an ultimate goal. Along with many other challenges, accurate segmentation of the chromosomes has been a major challenge especially due to the non rigid nature of the chromosomes. The earlier reported approaches for the segmentation have limited success as they are sensitive to scale variation, experimented only on gray images, unable to segment the clusters and the highly bent chromosomes. This work, describes an effective approach of segmentation of chromosomes in Metaphase images using Random Walker Algorithm [RWA] which is yet unexplored and not reported in the literature. The efforts are also done to compare the results with traditional methods so as to prove the efficiency of the implemented RWA algorithm. The algorithm is tested on publically available database and has shown encouraging and acceptable results. (6 pages)